Literature Review on Big Data Analytics and Demand Modeling in Supply Chain

New digital technologies have been introduced into our business and social environments, causing a major change that is recognized as the digital transformation in recent years. While environmental shifts suggest that most of the organization starts using advanced technologies such as Internet of Things (IoT), Mobile applications, Blackchain, Intelligence Things, catboats and many more in their supply chain planning to gain an early competitive advantage and these technologies generates enormous amount of data that the traditional business intelligence system difficult to handle processing of vast data in real-time or nearly real time causes abstraction to the insight discovery, demand modeling and supply chain optimization, Big Data initiatives for demand modeling and supply chain optimization promise to answer these challenges by incorporating various services, methods and tools for more agile and adaptably analytics and decision making, there by this paper focus on reviewing the level of analytics and the forecasting methods being used in the supply chain, understating the fundamentals of supply chain and role of demand modeling, there by proposing a high level framework for supply chain analytics in the context of big data with the knowledge of data science, artificial intelligence, big data echo system and supply chain.